Because I always believe that Pareto Principle applies in most aspect of computing: https://en.wikipedia.org/wiki/Pareto_principle https://en.wikipedia.org/wiki

Because I always believe that Pareto Principle applies in most aspect of computing: https://en.wikipedia.org/wiki/Pareto_principle https://en.wikipedia.org/wiki/Pareto_principle, I believe it'll also apply on this case too, and I find that it tracks with the progress of LLM/AIs. Breaking over 80% accuracy and solving the rest of 20% problem will be the main challenge of next-gen (or next-2gen) LLM, not to mention they still have tasks to bring down the computing costs. EDIT: that said, solving 80% of problems with 80% of accuracy with significant time saving is a solution that's worth to account, though we need to keep sceptical because the rest 20% may be gotten much worse because the 80% solved is in bad quality.